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Java实现的一个简单HashMap(翻译)

如何创建Hash表

对于把K(键)-V(值)这样的键值对插入Hash表中,需要执行两个步骤:

  1. 使用散列函数将K转换为小整数(称为其哈希码)。
  2. 哈希码用于查找索引(hashCode%arrSize),并且首先搜索该索引处的整个链表(单独链)以查找已存在的K。
  3. 如果找到,则更新其值,如果不是,则将K-V对存储为列表中的新节点。

复杂性和负载因子

  • 第一步,所用时间取决于K和散列函数。

例如,如果键是字符串“abcd”,那么它的散列函数可能取决于字符串的长度。 但是对于非常大的n值,与n相比,映射中的条目数,密钥的长度几乎可以忽略不计,因此可以认为散列计算在恒定时间内发生,即O(1)。

  • 对于第二步,需要遍历存在于该索引处的K-V对列表。 为此,最坏的情况可能是所有n个条目都在相同的索引处。 因此,时间复杂度将是O(n)。 但是,已经进行了足够的研究以使散列函数产生的键在数组中均匀分布,因此这几乎不会发生。
  • 因此,平均而言,如果有n个条目且b是数组的大小,则每个索引上将有n / b个条目。 此值n / b称为负载因子,表示hash表上的负载情况。
  • 该负载因子(Load Factor)需要保持较低,因此一个索引处的条目数较少,因此复杂度几乎恒定,即O(1)。

Rehashing

顾名思义,rehashing意味着再次散列。 基本上,当负载因子增加到超过其预定值(负载因子的默认值为0.75)时,复杂性就会增加。因此,为了克服这个问题,数组的大小增加(加倍)并且所有值再次进行散列并存储在新的双倍大小的数组中,以保持低负载因子和低复杂度。

为什么要Rehashing

进行重新散列是因为每当将键值对插入到映射中时,负载因子增加,这意味着时间复杂度也如上所述地增加。 这可能无法提供O(1)所需的时间复杂度。

因此,必须进行重新散列,增加Bucket Array的大小,以减少负载因子和时间复杂度。

如何Rehashing

可以按如下方式进行Rehashing:

  • 对于每次向hash表添加新条目,请检查负载因子。
  • 如果它大于其预定义值(如果没有给出,则默认值为0.75),然后重新散列。
  • 对于Rehashing,创建一个比以前大小加倍的新数组,并使其成为新的Bucket Array。
  • 然后遍历旧Bucket Array中的每个元素,并为每个元素调用insert()函数,以便将其插入到新的更大的bucket数组中。

Java程序实例

// Java program to implement Rehashing 

import java.util.ArrayList; 

class Map<K, V> { 

    class MapNode<K, V> { 

        K key; 
        V value; 
        MapNode<K, V> next; 

        public MapNode(K key, V value) 
        { 
            this.key = key; 
            this.value = value; 
            next = null; 
        } 
    } 

    // The bucket array where 
    // the nodes containing K-V pairs are stored 
    ArrayList<MapNode<K, V> > buckets; 

    // No. of pairs stored - n 
    int size; 

    // Size of the bucketArray - b 
    int numBuckets; 

    // Default loadFactor 
    final double DEFAULT_LOAD_FACTOR = 0.75; 

    public Map() 
    { 
        numBuckets = 5; 

        buckets = new ArrayList<>(numBuckets); 

        for (int i = 0; i < numBuckets; i++) { 
            // Initialising to null 
            buckets.add(null); 
        } 
        System.out.println("HashMap created"); 
        System.out.println("Number of pairs in the Map: " + size); 
        System.out.println("Size of Map: " + numBuckets); 
        System.out.println("Default Load Factor : " + DEFAULT_LOAD_FACTOR + "/n"); 
    } 

    private int getBucketInd(K key) 
    { 

        // Using the inbuilt function from the object class 
        int hashCode = key.hashCode(); 

        // array index = hashCode%numBuckets 
        return (hashCode % numBuckets); 
    } 

    public void insert(K key, V value) 
    { 
        // Getting the index at which it needs to be inserted 
        int bucketInd = getBucketInd(key); 

        // The first node at that index 
        MapNode<K, V> head = buckets.get(bucketInd); 

        // First, loop through all the nodes present at that index 
        // to check if the key already exists 
        while (head != null) { 

            // If already present the value is updated 
            if (head.key.equals(key)) { 
                head.value = value; 
                return; 
            } 
            head = head.next; 
        } 

        // new node with the K and V 
        MapNode<K, V> newElementNode = new MapNode<K, V>(key, value); 

        // The head node at the index 
        head = buckets.get(bucketInd); 

        // the new node is inserted 
        // by making it the head 
        // and it's next is the previous head 
        newElementNode.next = head; 

        buckets.set(bucketInd, newElementNode); 

        System.out.println("Pair(" + key + ", " + value + ") inserted successfully./n"); 

        // Incrementing size 
        // as new K-V pair is added to the map 
        size++; 

        // Load factor calculated 
        double loadFactor = (1.0 * size) / numBuckets; 

        System.out.println("Current Load factor = " + loadFactor); 

        // If the load factor is > 0.75, rehashing is done 
        if (loadFactor > DEFAULT_LOAD_FACTOR) { 
            System.out.println(loadFactor + " is greater than " + DEFAULT_LOAD_FACTOR); 
            System.out.println("Therefore Rehashing will be done./n"); 

            // Rehash 
            rehash(); 

            System.out.println("New Size of Map: " + numBuckets + "/n"); 
        } 

        System.out.println("Number of pairs in the Map: " + size); 
        System.out.println("Size of Map: " + numBuckets + "/n"); 
    } 

    private void rehash() 
    { 

        System.out.println("/n***Rehashing Started***/n"); 

        // The present bucket list is made temp 
        ArrayList<MapNode<K, V> > temp = buckets; 

        // New bucketList of double the old size is created 
        buckets = new ArrayList<MapNode<K, V> >(2 * numBuckets); 

        for (int i = 0; i < 2 * numBuckets; i++) { 
            // Initialised to null 
            buckets.add(null); 
        } 
        // Now size is made zero 
        // and we loop through all the nodes in the original bucket list(temp) 
        // and insert it into the new list 
        size = 0; 
        numBuckets *= 2; 

        for (int i = 0; i < temp.size(); i++) { 

            // head of the chain at that index 
            MapNode<K, V> head = temp.get(i); 

            while (head != null) { 
                K key = head.key; 
                V val = head.value; 

                // calling the insert function for each node in temp 
                // as the new list is now the bucketArray 
                insert(key, val); 
                head = head.next; 
            } 
        } 

        System.out.println("/n***Rehashing Ended***/n"); 
    } 

    public void printMap() 
    { 

        // The present bucket list is made temp 
        ArrayList<MapNode<K, V> > temp = buckets; 

        System.out.println("Current HashMap:"); 
        // loop through all the nodes and print them 
        for (int i = 0; i < temp.size(); i++) { 

            // head of the chain at that index 
            MapNode<K, V> head = temp.get(i); 

            while (head != null) { 
                System.out.println("key = " + head.key + ", val = " + head.value); 

                head = head.next; 
            } 
        } 
        System.out.println(); 
    } 
} 

public class GFG { 

    public static void main(String[] args) 
    { 

        // Creating the Map 
        Map<Integer, String> map = new Map<Integer, String>(); 

        // Inserting elements 
        map.insert(1, "Geeks"); 
        map.printMap(); 

        map.insert(2, "forGeeks"); 
        map.printMap(); 

        map.insert(3, "A"); 
        map.printMap(); 

        map.insert(4, "Computer"); 
        map.printMap(); 

        map.insert(5, "Portal"); 
        map.printMap(); 
    } 
}

运行输出

HashMap created
Number of pairs in the Map: 0
Size of Map: 5
Default Load Factor : 0.75

Pair(1, Geeks) inserted successfully.

Current Load factor = 0.2
Number of pairs in the Map: 1
Size of Map: 5

Current HashMap:
key = 1, val = Geeks

Pair(2, forGeeks) inserted successfully.

Current Load factor = 0.4
Number of pairs in the Map: 2
Size of Map: 5

Current HashMap:
key = 1, val = Geeks
key = 2, val = forGeeks

Pair(3, A) inserted successfully.

Current Load factor = 0.6
Number of pairs in the Map: 3
Size of Map: 5

Current HashMap:
key = 1, val = Geeks
key = 2, val = forGeeks
key = 3, val = A

Pair(4, Computer) inserted successfully.

Current Load factor = 0.8
0.8 is greater than 0.75
Therefore Rehashing will be done.


***Rehashing Started***

Pair(1, Geeks) inserted successfully.

Current Load factor = 0.1
Number of pairs in the Map: 1
Size of Map: 10

Pair(2, forGeeks) inserted successfully.

Current Load factor = 0.2
Number of pairs in the Map: 2
Size of Map: 10

Pair(3, A) inserted successfully.

Current Load factor = 0.3
Number of pairs in the Map: 3
Size of Map: 10

Pair(4, Computer) inserted successfully.

Current Load factor = 0.4
Number of pairs in the Map: 4
Size of Map: 10


***Rehashing Ended***

New Size of Map: 10

Number of pairs in the Map: 4
Size of Map: 10

Current HashMap:
key = 1, val = Geeks
key = 2, val = forGeeks
key = 3, val = A
key = 4, val = Computer

Pair(5, Portal) inserted successfully.

Current Load factor = 0.5
Number of pairs in the Map: 5
Size of Map: 10

Current HashMap:
key = 1, val = Geeks
key = 2, val = forGeeks
key = 3, val = A
key = 4, val = Computer
key = 5, val = Portal

原文链接

原文  https://segmentfault.com/a/1190000020254131
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